Hostname: page-component-7b7567c8c-7pwfn Total loading time: 0 Render date: 2026-11-12T21:07:58.466Z Has data issue: false hasContentIssue false
  • English
  • Français

Dynamic modeling and parameter estimation for traction, rolling, and lateral wheel forces to enhance mobile robot trajectory tracking

Published online by Cambridge University Press:  03 June 2014

Gokhan Bayar,
A. Bugra Koku and
E. Ilhan Konukseven
Gokhan Bayar*
Affiliation:
Mechanical Engineering Department, Middle East Technical University, Ankara, Turkey E-mails: kbugra@metu.edu.tr, konuk@metu.edu.trMechanical Engineering Department, Bulent Ecevit University, Zonguldak, Turkey
A. Bugra Koku
Affiliation:
Mechanical Engineering Department, Middle East Technical University, Ankara, Turkey E-mails: kbugra@metu.edu.tr, konuk@metu.edu.tr
E. Ilhan Konukseven
Affiliation:
Mechanical Engineering Department, Middle East Technical University, Ankara, Turkey E-mails: kbugra@metu.edu.tr, konuk@metu.edu.tr
*
*Corresponding author. E-mail: gbayar@gmail.com
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

Studying wheel and ground interaction during motion has the potential to increase the performance of localization, navigation, and trajectory tracking control of a mobile robot. In this paper, a differential mobile robot is modeled in a way that (traction, rolling, and lateral) wheel forces are included in the overall system dynamics. Lateral wheel forces are included in the mathematical model together with traction and rolling forces. A least square parameter estimation process is proposed to estimate the parameters of the wheel forces. In order to implement the proposed methodologies, an experimental setup is used. The setup contains a differentially driven mobile robot, a specially constructed test surface, and a camera system attached at the top of surface for obtaining ground truth. Models having one or more wheel forces are simulated to find the most realistic model. Simulation results are verified by experiments.

Keywords

Mobile robotDifferential driveWheel forcesParameter estimation

Information

Type
Articles
Information
Robotica , Volume 33 , Issue 10 , December 2015, pp. 2204 - 2220
Copyright
Copyright © Cambridge University Press 2014 

References

1. Motte, I. and Campion, G. “A slow manifold approach for the control of mobile robots not satisfying the kinematic constraints,” IEEE Trans. Robot. Autom. 16 (6), 875–880 (2000).Google Scholar
2. Ward, C. C. and Iagnemma, K., “A dynamic-model-based wheel slip detector for mobile robots on outdoor terrain,” IEEE Trans. Robot. 24 (4), 821–831 (2008).Google Scholar
3. Tian, Y., Sidek, N. and Sarkar, N., “Modeling and Control of a Nonholonomic Wheeled Mobile Robot with Wheel Slip Dynamics,” Proceedings of the IEEE Symposium on Computational Intelligence in Control and Automation, Nashville, USA (Mar. 30–Apr. 2, 2009) pp. 7–14.Google Scholar
4. Sidek, N. and Sarkar, N., “Inclusion of Wheel Slips in Mobile Robot Modeling to Enhance Robot Simulator Performance,” Proceedings of the 3rd International Conference on Mechatronics, Kuala Lumpur, Malaysia (Dec. 18–20, 2008).Google Scholar
5. Caracciolo, L., Luca, A. D. and Iannitti, S., “Trajectory Tracking Control of a Four Wheel Differentially Driven Mobile Robot,” Proceedings of the IEEE International Conference on Robotics & Automation, Detroit, USA (May 10–15, 1999) pp. 2632–2638.Google Scholar
6. Li, L., Wang, F. Y. and Zhou, Q., “Integrated longitudinal and lateral tire/road friction modeling and monitoring for vehicle motion control,” IEEE Trans. Intell. Transp. Syst. 7 (1), 1–19 (2006).Google Scholar
7. Yi, J., Song, D., Zhang, J. and Goodwin, Z., “Adaptive Trajectory Tracking Control of Skid Steering Mobile Robot,” Proceedings of the IEEE International Conference on Robotics and Automation, Rome, Italy (Apr. 10–14, 2007) pp. 2605–2610.Google Scholar
8. Balakrishna, R. and Ghosal, A., “Modeling of slip for wheeled mobile robots,” IEEE Trans. Robot. Autom. 11 (1), 126–132 (1995).Google Scholar
9. Williams, R. L., Carter, B. E., Gallina, P. and Rosati, G., “Dynamic model with slip for wheeled omnidirectional robots,” IEEE Trans. Robot. Autom. 18 (3), 285–293 (2002).Google Scholar
10. Wong, J. Y., Theory of Ground Vehicles, 3rd ed. (John Wiley & Sons, Inc., New York, US, 2001).Google Scholar
11. Yun, X., “State Space Representation of Holonomic and Nonholonomic Constraints Resulting from Rolling Contacts,” Proceedings of the IEEE International Conference on Robotics and Automation, Nagoya, Japan (May 21–27, 1995) pp. 2690–2694.Google Scholar
12. Ray, L. E., “Autonomous Terrain Parameter Estimation for Wheeled Vehicles,” In: Unmanned Systems Technology X, Proceedings of SPIE—the International Society for Optical Engineering, vol. 6962, Orlando, USA (Mar. 17–20, 2008) pp. 6962–6974.Google Scholar
13. Iagnemma, K. and Dubowsky, S., “Terrain Estimation for High Speed Rough Terrain Autonomous Vehicle Navigation,” In: Unmanned Ground Vehicle Technology IV, Proceedings of SPIE—the International Society for Optical Engineering, vol. 4715, Orlando, USA (Apr. 2–3, 2002) pp. 256–266.Google Scholar
14. Ojeda, L., Borenstein, J., Witus, G. and Karlsen, R., “Terrain characterization and classification with a mobile robot,” J. Field Robot. 23 (2), 103–122 (2006).Google Scholar
15. Song, Z., Hutangkabodee, S., Zweiri, Y. H., Seneviratne, L. D. and AIthoefer, K., “Identification of Soil Parameters for Unmanned Ground Vehicles Track-Terrain Interaction Dynamics,” Proceedings of the SICE Annual Conference, Sapporo, Japan (Aug. 4–6, 2004) pp. 2255–2260.Google Scholar
16. Wit, C. C. D. and Tsiotras, P., “Dynamic Tire Friction Models for Vehicle Traction Control,” Proceedings of the 38th IEEE Conference on Decision and Control, Phoenix, USA (1999).Google Scholar
17. Han, J., Sun, Y., Meng, C. and Han, J., “Estimating the Tire Road Friction for Tire Pressure Monitoring using the Result of a Nonlinear Observer,” Proceedings of the 7th World Congress on Intelligent Control and Automation, Chongqing, China (Jun. 25–27, 2008) pp. 1982–1985.Google Scholar
18. Ishigami, G., Miwa, A., Magatani, K. and Yoshida, K., “Terramechanics-based model for steering maneuver of planetary exploration rovers on loose soil,” J. Field Robot. 24 (3), 233–250 (2007).Google Scholar
19. Yun, X. and Yamamoto, Y., “Internal Dynamics of a Wheeled Mobile Robot,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Yokohama, Japan (Jul. 26–30, 1993) pp. 1288–1294.Google Scholar
20. Salerno, A. and Angeles, J., “A new family of two wheeled mobile robots: Modeling and controllability,” IEEE Trans. Robot. 23 (1), 169–173 (2007).Google Scholar
21. Ploeg, J., Schouten, H. E. and Nijmeijer, H., “Control Design for a Mobile Robot Including Tire Behavior,” IEEE Intelligent Vehicles Symposium, Eindhoven, The Netherlands (Jun. 4–6, 2008) pp. 240–245.Google Scholar
22. Pacejka, H. B., Tire and Vehicle Dynamics, 2nd ed. (Elsevier, Burlington, MA, US, 2006).Google Scholar
23. Bekker, M. G., Theory of Land Locomotion: the Mechanics of Vehicle Mobility (University of Michigan Press, Ann Arbor, Michigan, 1956).Google Scholar
24. Bakker, E., Nyborg, L. and Pacejka, H. B., “Tyre modelling for use in vehicle dynamic studies,” Society of Automotive Engineers, paper 870421 (1987).Google Scholar
25. Bakker, E., Pacejka, H. B. and Lidner, L., “A new tire model with an application in vehicle dynamic studies,” Society of Automotive Engineers, paper 890087 (1989).Google Scholar
26. Pacejka, H. B., “The Tyre as a Vehicle Component,” Proceedings of the 26th FISITA Congress, Prague, Czech Republic (Jun. 16–23, 1996) pp. 1–19.Google Scholar
27. Pacejka, H. B. and Besselink, I. J. M., “Magic Formula Tyre Model with Transient Properties,” Proceedings of the 2nd International Colloquium on Tyre Models for Vehicle Dynamic Analysis, Berlin, Germany (Feb. 20–21, 1997) pp. 145–155.Google Scholar
28. Yun, X. and Yamamoto, Y., “Stability analysis of the internal dynamics of a wheeled mobile robot,” J. Robot. Syst. 14 (10), 697–709 (1997).Google Scholar